Literature DB >> 31364989

Profiling the Escherichia coli membrane protein interactome captured in Peptidisc libraries.

Michael Luke Carlson1, R Greg Stacey2, John William Young1, Irvinder Singh Wason1, Zhiyu Zhao1, David G Rattray2, Nichollas Scott2, Craig H Kerr2, Mohan Babu3, Leonard J Foster2, Franck Duong Van Hoa1.   

Abstract

Protein-correlation-profiling (PCP), in combination with quantitative proteomics, has emerged as a high-throughput method for the rapid identification of dynamic protein complexes in native conditions. While PCP has been successfully applied to soluble proteomes, characterization of the membrane interactome has lagged, partly due to the necessary use of detergents to maintain protein solubility. Here, we apply the peptidisc, a 'one-size fits all' membrane mimetic, for the capture of the Escherichia coli cell envelope proteome and its high-resolution fractionation in the absence of detergent. Analysis of the SILAC-labeled peptidisc library via PCP allows generation of over 4900 possible binary interactions out of >700,000 random associations. Using well-characterized membrane protein systems such as the SecY translocon, the Bam complex and the MetNI transporter, we demonstrate that our dataset is a useful resource for identifying transient and surprisingly novel protein interactions. For example, we discover a trans-periplasmic supercomplex comprising subunits of the Bam and Sec machineries, including membrane-bound chaperones YfgM and PpiD. We identify RcsF and OmpA as bone fide interactors of BamA, and we show that MetQ association with the ABC transporter MetNI depends on its N-terminal lipid anchor. We also discover NlpA as a novel interactor of MetNI complex. Most of these interactions are largely undetected by standard detergent-based purification. Together, the peptidisc workflow applied to the proteomic field is emerging as a promising novel approach to characterize membrane protein interactions under native expression conditions and without genetic manipulation.
© 2019, Carlson et al.

Entities:  

Keywords:  E. coli; Peptidisc; SILAC; SMALPs; biochemistry; chemical biology; computational biology; membrane protein complexes; membrane proteomics; systems biology

Mesh:

Substances:

Year:  2019        PMID: 31364989      PMCID: PMC6697469          DOI: 10.7554/eLife.46615

Source DB:  PubMed          Journal:  Elife        ISSN: 2050-084X            Impact factor:   8.140


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